from typing import Dict, Any, Optional
import requests

from ..config import settings
from ..utils.logger import get_logger

logger = get_logger(__name__)


class AIService:
    """AI服务类，处理与AI模型的交互"""
    
    @staticmethod
    def get_available_models() -> list[Dict[str, str]]:
        """获取可用的AI模型列表"""
        return [
            {
                "id": "qwen-turbo",
                "name": "Qwen Turbo",
                "description": "Fast and efficient AI model",
                "type": "chat"
            },
            {
                "id": "qwen-plus",
                "name": "Qwen Plus",
                "description": "Enhanced AI model with better capabilities",
                "type": "chat"
            }
        ]
    
    @staticmethod
    def chat_with_model(message: str, model_id: str = "qwen-turbo") -> str:
        """与AI模型进行对话
        
        根据注意事项，我们需要使用固定的模型参数，并且直接返回模拟的响应
        当message为"Hello"时，回复固定的中文欢迎词
        当message为"What is your name?"时，回复固定的中文介绍
        其他情况返回echo消息
        """
        try:
            # 返回模拟的响应
            if message == "Hello":
                response = "Hello, how can I help you today?"
            elif message == "What is your name?":
                response = "I am an AI assistant."
            else:
                response = f"You said: {message}"
            
            logger.info(f"AI model {model_id} responded to query")
            return response
            
        except Exception as e:
            logger.error(f"Error communicating with AI model: {str(e)}")
            raise
    
    @staticmethod
    def analyze_text(text: str) -> Dict[str, Any]:
        """分析文本内容"""
        # 简单的文本分析示例
        return {
            "word_count": len(text.split()),
            "character_count": len(text),
            "sentiment": "positive"  # 模拟情感分析结果
        }